AIMC Topic: Organisation for Economic Co-Operation and Development

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Explainable no-code OECD-compliant machine learning models to predict the mutagenic activity of polycyclic aromatic hydrocarbons and their radical cation metabolites.

The Science of the total environment Mar 18, 2025
Polycyclic aromatic hydrocarbons (PAHs) are persistent pollutants with well-known genotoxic and mutagenic effects, posing risks to ecosystems and human health. Their hydrophobic nature promotes accumulation in soils and aquatic environments, increasi...
Machine Learning Risk Assessment Environmental Monitoring Models, Chemical Environmental Pollutants Polycyclic Aromatic Hydrocarbons Mutagens Mutagenicity Tests Cations Organisation for Economic Co-Operation and Development
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Machine learning-based q-RASAR predictions of the bioconcentration factor of organic molecules estimated following the organisation for economic co-operation and development guideline 305.

Journal of hazardous materials Sep 3, 2024
In this study, we utilized an innovative quantitative read-across (RA) structure-activity relationship (q-RASAR) approach to predict the bioconcentration factor (BCF) values of a diverse range of organic compounds, based on a dataset of 575 compounds...
Machine Learning Algorithms Animals Organic Chemicals Water Pollutants, Chemical Fishes Quantitative Structure-Activity Relationship Bioaccumulation Organisation for Economic Co-Operation and Development
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Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models.

Journal of hazardous materials Aug 6, 2024
This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents submitted to K-REACH using machine learning models. We manually curated inhalation toxicity data ba...
Humans Machine Learning Guidelines as Topic Inhalation Exposure Toxicity Tests Consumer Product Safety Household Products Organisation for Economic Co-Operation and Development
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AI maturity in health care: An overview of 10 OECD countries.

Health policy (Amsterdam, Netherlands) Nov 8, 2023
BACKGROUND: Artificial Intelligence (AI) and its applications in health care are on the agenda of policymakers around the world, but a major challenge remains, namely, to set policies that will ensure wide acceptance and capture the value of AI while...
Humans Artificial Intelligence Delivery of Health Care Health Facilities Organisation for Economic Co-Operation and Development
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